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Record W4280489959 · doi:10.1093/jcr/ucac023

Dysplacement and the Professionalization of the Home

2022· article· en· W4280489959 on OpenAlexaff
Annetta Grant, Jay M. Handelman

Bibliographic record

VenueJournal of Consumer Research · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCulinary Culture and Tourism
Canadian institutionsQueen's University
Fundersnot available
KeywordsMeaning (existential)ProfessionalizationAsset (computer security)SociologyPublic relationsIdentity (music)Aging in placeSense of placeDynamics (music)EthnographyPersonalizationMarketingBusinessPsychologyAestheticsPolitical scienceSocial scienceComputer science

Abstract

fetched live from OpenAlex

Abstract This research directs our attention to the dynamics surrounding the changing cultural understanding of the place we call home. Traditionally, the home is regarded as a place of singularization that is to be aligned with the homeowner’s unique identity. This traditional meaning has come to be confronted with a contradictory understanding of the home as a marketplace asset. Homeowners come to experience a market-reflected gaze that shuns singularization while driving homeowners to exhibit expertise in aligning their homes with marketplace standards. Professionalization of the home, through marketplace expertise and standardization, discourages personalization, leading to an experience of disorientation with the place of home. In this ethnography of the home renovation marketplace, we build on the concept of ‘dysplacement’ whereby this contradictory cultural understanding of the home disrupts the homeowner’s ability to achieve implacement. The concept of dysplacement and the corresponding place disorientation experience has the potential to enrich our theoretical understanding of place by integrating the cultural meaning of place as a domain with marketplace dynamics and individual consumer practices surrounding place.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.522

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.057
GPT teacher head0.323
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations10
Published2022
Admission routes1
Has abstractyes

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